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Contributing to MLOps Mastery: Building Enterprise LLM Systems on Azure Databricks

Thank you for your interest in contributing to this MLOps playbook! This document provides guidelines and instructions for contributing.

Code of Conduct

By participating in this project, you agree to maintain a respectful and inclusive environment for everyone. Please report any unacceptable behavior to the project maintainers.

How to Contribute

Reporting Issues

If you find a bug or have a suggestion for improvement:

  1. Check if the issue already exists in the Issues section
  2. If not, create a new issue using the provided template
  3. Include a clear title and description
  4. Add relevant labels
  5. If possible, include steps to reproduce the issue or screenshots

Suggesting Enhancements

We welcome suggestions for enhancements! When suggesting:

  1. Use a clear and descriptive title
  2. Provide a detailed description of the proposed enhancement
  3. Explain why this enhancement would be useful
  4. Include any relevant examples or references

Pull Requests

  1. Fork the repository
  2. Create a new branch from main (git checkout -b feature/your-feature-name)
  3. Make your changes
  4. Run tests to ensure your changes don't break existing functionality
  5. Commit your changes with clear, descriptive commit messages
  6. Push to your branch
  7. Submit a pull request to the main branch

Pull Request Guidelines

  • Follow the coding style and conventions used in the project
  • Include tests for new features or bug fixes
  • Update documentation as needed
  • Keep pull requests focused on a single change
  • Link to any relevant issues

Development Setup

  1. Clone the repository
  2. Install dependencies: 
    pip install -r requirements.txt
  3. Set up pre-commit hooks: 
    pre-commit install

Coding Standards

  • Follow PEP 8 style guidelines for Python code
  • Use meaningful variable and function names
  • Write docstrings for all functions, classes, and modules
  • Add comments for complex logic

Testing

  • Add tests for new features
  • Ensure all tests pass before submitting a pull request
  • Run tests with: 
    pytest

Documentation

When adding or modifying features, please update the relevant documentation. This includes:

  • README.md
  • Code comments and docstrings
  • Diagram updates if necessary
  • Example notebooks if applicable

Review Process

All submissions require review. Maintainers will review your PR and may suggest changes or improvements. Please be responsive to feedback.

Thank You

Your contributions are what make this project better for everyone. Thank you for your time and effort!